Literature DB >> 28603583

SEGMENTATION OF MYOCARDIUM USING DEFORMABLE REGIONS AND GRAPH CUTS.

Mustafa Gökhan Uzunbaş1, Shaoting Zhang1, Kilian M Pohl2, Dimitris Metaxas1, Leon Axel3.   

Abstract

Deformable models and graph cuts are two standard image segmentation techniques. Combining some of their benefits, we introduce a new segmentation system for (semi-) automatic delineation of epicardium and endocardium of Left Ventricle of the heart in Magnetic Resonance Images (MRI). Specifically, a temporal information among consecutive phases is exploited via a coupling between deformable models and graph cuts which provides automated accurate cues for graph cuts and also good initialization scheme for deformable model that ultimately leads to more accurate and smooth segmentation results with lower interaction costs than using only graph cut segmentation. In addition, we define deformable model as a region defined by two nested contours and segment epicardium and endocardium in an unified way by optimizing single energy functional. This approach provides inherent coherency among the two contours thus leads to more accurate results than deforming separate contours for each target. We show promising results on the challenging problems of left ventricle segmentation.

Entities:  

Keywords:  Segmentation; deformable models; graph cuts; left ventricle

Year:  2012        PMID: 28603583      PMCID: PMC5463182          DOI: 10.1109/ISBI.2012.6235532

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  3 in total

1.  Automated segmentation of the left ventricle in cardiac MRI.

Authors:  Michael R Kaus; Jens von Berg; Jürgen Weese; Wiro Niessen; Vladimir Pekar
Journal:  Med Image Anal       Date:  2004-09       Impact factor: 8.545

2.  Coupled nonparametric shape and moment-based intershape pose priors for multiple basal ganglia structure segmentation.

Authors:  Mustafa Gökhan Uzunbaş; Octavian Soldea; Devrim Unay; Müjdat Cetin; Gözde Unal; Aytül Erçil; Ahmet Ekin
Journal:  IEEE Trans Med Imaging       Date:  2010-12       Impact factor: 10.048

3.  Model-based Graph Cut Method for Segmentation of the Left Ventricle.

Authors:  Xiang Lin; Brett Cowan; Alistair Young
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2005
  3 in total
  3 in total

1.  Hierarchical Vertex Regression-Based Segmentation of Head and Neck CT Images for Radiotherapy Planning.

Authors: 
Journal:  IEEE Trans Image Process       Date:  2018-02       Impact factor: 10.856

2.  Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network.

Authors:  Zakarya Farea Shaaf; Muhammad Mahadi Abdul Jamil; Radzi Ambar; Ahmed Abdu Alattab; Anwar Ali Yahya; Yousef Asiri
Journal:  Diagnostics (Basel)       Date:  2022-02-05

3.  BgCut: automatic ship detection from UAV images.

Authors:  Chao Xu; Dongping Zhang; Zhengning Zhang; Zhiyong Feng
Journal:  ScientificWorldJournal       Date:  2014-04-03
  3 in total

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